Introducing Product Recommendations

MailChimp’s mission has always been to empower small businesses. Our Automation, reporting, and Multivariate Testing features are designed to be both easy to use and powerful, because even the smallest business should have a few power tools in their shed.

One such tool that’s usually reserved for larger e-commerce businesses is automatic product recommendations based on customers’ previous purchases. You probably interact with these every day. Amazon puts them all over, from your homepage to your shipping confirmation, and Netflix knows if you’re more likely to enjoy Master of None or Fuller House. But Amazon and Netflix are giants. Small businesses can’t do product recommendations, right? It requires data, math, and infrastructure, and a whole bunch of other boring things that most people don’t want to think about.

Here’s how Product Recommendations work…

But that’s all we know. We can segment campaigns and trigger Automation workflows with this data, but we’d still have to figure out what to say. It’d be great if we could use this order to guess what Tonee’s next likely purchase would be. Then we could send an email about that product.

OK, cool. I bet the data will tell us what product to recommend. Sounds easy, right? Let’s visualize all of the customers and orders from our fake store:

Maybe that’s not so easy to understand. There’s a lot going on, and it takes time and effort to make sense of all of this data. Fortunately, we can do some math to identify important trends.

It turns out that people who buy the shirt often buy the socks and, to a lesser extent, the hat. They’re also not into the cards, action figure, or books. Just like that, we’ve turned our purchase data into actionable information. Now, we can recommend the socks and hat to Tonee in our next campaign.

But wait, what if a subscriber hasn’t bought anything? In that case, they’ll receive a list of items that have been selling well lately, and nobody will receive a recommendation for something that they’ve already bought or that was out of stock when the recommendation was generated.

Product Recommendations are based on this general idea, but they’re a bit more complicated than that in practice. They’re even more complicated if you have thousands of products and customers, but fear not—if your store is connected, we’ll take care of the hard part.

…and here’s where it gets technical

We know our product recommendations model works because we’ve been testing it behind the scenes. We tested using the data of millions of customers, products, and orders across our e-commerce customers and made product recommendations based on that data. Then, we compared our product recommendations as well as random product selections to actual purchases using a metric called Discounted Cumulative Gain (DCG). Then, we plotted the median recommendation-to-random DCG ratio for each store. A value above 1 indicates that we learned something about customer preferences and successfully predicted future purchases.

Custom recommendations were able to predict future purchases more than 98% of the time. We also used this data to set criteria that a store must meet before they get recommendations. Here’s what your store needs in order to use Product Recommendations:

More than 50 different customers in the past year

More than 10 available products

More than 500 orders in the past year

But! For newer stores or stores that don’t otherwise meet this criteria, you can still send top sellers instead of custom recommendations.

Start recommending

To get started, you’ll need to upload e-commerce data that has product images, links, and inventory amounts. Our Shopify and BigCommerce integrations will do this for you, but you can also do it yourself with the MailChimp API. Our Magento integration, available for download on June 7, 2016, will also offer these features.

We hope Product Recommendations will help you break into the world of data-driven marketing. Above all else, we think your data should help you make smarter decisions, not overwhelm you. We hope that our new tool will save you time and increase your revenue by effortlessly generating content that simply makes sense. Let us know how it works once you’ve tried it out.

We build addons for PrestaShop, which is The #1 e-commerce platform in Europe. How can we get technical documentation to build an integration for PrestaShop ? By the way, we use MailChimp ourselves for our newsletters and love you guys ;)

Hi David!
A good start would be to read our API documentation. Here is a link to the section on e-commerce data: http://eepurl.com/bUb8iH

We are working on some guides to integrating a shop with MailChimp. If you would like to read these guides when they are ready, your best bet would be to subscribe to the MailChimp API newsletter: http://eepurl.com/bE-IXv

We are a Magento shop and have had success with the eBizmarts plug in. Your blog post states there that “Our Magento integration, available for download on June 7, 2016, will also offer these features.” I followed the links and it took me to eBizmarts MageMonkey plug in v1.2.2 which we already use — and it has not been updated since February. Am I missing something? thanks!

I just asked some of our devs about this, and they recommended using both for the time being. They also said to make sure they were synced up to the same list. That will give you the best feature coverage and access to tools like product recommendations and abandoned cart notifications. At some point down the line, only the newest integration will be needed.

Hey Doug, we recommend you stay on the Magemonkey plugin if you are utilizing their abandoned cart or transactional email features. Once we release those features for MailChimp for Magento, you should upgrade. Thanks!

I found this link: http://kb.mailchimp.com/integrations/e-commerce/connect-mailchimp-for-magento Where it says: “If you’re already using MageMonkey, you must uninstall MageMonkey before you can use MailChimp for Magento.” Many of us use this older extension, and MailChimp is an important part of our ecom strategy. Please re-confirm they can co-exist or elaborate on why this KB article is wrong. Thanks Neel, Doug

Hey Todd,
We make all recommendations at the variant level. If we think that a customer would like two variants of a product, we only show them the variant that we are more confident in. Additionally, we are considering variant-level stock and orders when we omit out-of-stock or previously-purchased items from a customer’s recommendations.

Hey Noah,
We don’t currently have the ability to blacklist products from recommendations, but we are considering that ability for future updates. In the meantime, it is worth noting that products that have <=0 inventory quantity should not show up in recommendations. Thanks for your patience, and we'll be sure to let our users know about future updates to the Product Recommendations tool.

Absolutely! We try to take all feedback into account. If you utilize the inventory quantities to hide items from recommendations, please keep in mind that they might not be removed from recommendations until next Monday.

I am trying to set up now but when i show 2 product suggestions the same product comes up. cant figure out how to change it – have tried adjusting the range to display but all options i am given still display the same item twice..
any clues?
also I am a brand new store, have only made one sale, will this even work and what will show up for my customers? When i send test emails to myself the products are blank still..

Hey Sarah,
If you have very few orders, we will only show top sellers. If you do not have enough sales to show top sellers, we should be showing random products. I’ll take a look at your recommendations and let you know what I find, but I would recommend holding off on using product recommendations until you have a couple of months of sales.